| Autor: |
Youshu Cheng, Biao Cai, Hongyu Li, Xinyu Zhang, Gypsyamber D’Souza, Sadeep Shrestha, Andrew Edmonds, Jacquelyn Meyers, Margaret Fischl, Seble Kassaye, Kathryn Anastos, Mardge Cohen, Bradley E. Aouizerat, Ke Xu, Hongyu Zhao |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Genome Biology, Vol 25, Iss 1, Pp 1-27 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1474-760X |
| DOI: |
10.1186/s13059-024-03411-7 |
| Popis: |
Abstract Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk methylation datasets composed of different cell types and limit our understanding of cell-type-specific methylation regulation. We propose a hierarchical Bayesian interaction (HBI) model to infer cell-type-specific meQTLs, which integrates a large-scale bulk methylation data and a small-scale cell-type-specific methylation data. Through simulations, we show that HBI enhances the estimation of cell-type-specific meQTLs. In real data analyses, we demonstrate that HBI can further improve the functional annotation of genetic variants and identify biologically relevant cell types for complex traits. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full text from SpringerLink